Carbon footprint of the nuclear energy using IO-LCA Jorge E. Zafrilla a, María Ángeles Cadarso a, Fabio Monsalve a y Cristina de la Rúa b a Universidad

Carbon footprint of the nuclear energy using IO-LCAJorge E. Zafrillaa, María Ángeles Cadarsoa, Fabio Monsalvea y Cristina de la Rúab

a Universidad de Castilla-La Mancha, Albaceteb Centro de Investigaciones Energéticas, Medioambientales y Tecnológicas

E-mail: [email protected]

IX Congreso Asociación Española para la Economía Energética

Madrid, 3 y 4 de febrero de 2014

IX Congreso de la Asociación Española para la Economía EnergéticaMadrid, 3 y 4 de febrero de 2014

Outline

1. Introduction2. 2.1. Data

2.2. Methodology 2.3. Scenarios

3. Main results4. Conclusions

1. Introduction

Energy Roadmap 2050 establishes an 80-95% GHG reduction by 2050 within the EU.

One of the main targets is to turn the electricity sector in a quasi-zero emissions sector.

Nuclear power could play an important role in the fulfilling of environmental commitments.

The main objective is to develop a MRIO-LCA model for a nulcear power plant in Spain under different scenarios

analyzing the carbon footprint of the facility

But, how clean is nuclear power from an IO-LCA perspective?


Financial comparisons

SRIO / MRIO / hMRIO-LCA

Construction period

Lifetime

Load Factor

GHG intensities

Consumption patterns

Uranium prices

1. Introduction

a) The data set and the methodology allow us to estimate the variability and the uncertainties of the analysis via multiple scenarios.

Contributions

Methodological

Technical

Political

Financial

SCENARIOS


1. Introduction

b) The use of the MRIO-LCA model to face the problems related to emissions linked to production processes of imported goods.

Contributions

c) This is the first study of nuclear power carbon footprint in Spain.

The case of nuclear power is special because Spain does not have a covering

industry behind the nuclear power. It has to import a big amount of inputs in the production

process.


2.1. Data

The MRIO model is based on WIOD.

The technical and sectorial data set is provided by Spanish Nuclear Industry Forum.Ruesga, S.M. (2008). “Análisis económico de un proyecto

de ampliación de la producción eléctrica nuclear” Nucler power LCA phases differentiation:

1) Construction/Investment 2) Nuclear Fuel cycle (fuel decommissioning included)

3) Operation & Maintenance (facility dismantle phase

is included)


2.1. Data

Years Investment activity %/Total M€uros Allowances (7513)

Civil Enineering

(35500)

EG Mechan

ical (291)

EG Electric (311)

Buildings and CE (452)

Insuarances

(66031)IMPORTS

1 allowance 2% 49,00 49,00 0,00 0,00 0,00 0,00 0,00 0,002 allowance 2% 49,00 49,00 0,00 0,00 0,00 0,00 0,00 0,003 civil engineering 10% 245,00 0,00 163,33 40,83 40,83 0,00 0,00 0,004 equipments + ce 18% 441,00 0,00 114,33 40,83 40,83 0,00 0,00 245,005 equipments + ce 20% 490,00 0,00 114,33 81,67 81,67 40,83 0,00 212,336 equipments + ce 25% 612,50 0,00 40,83 81,67 81,67 36,75 4,08 367,507 equipments + ce 15% 367,50 0,00 40,83 122,50 81,67 32,67 8,17 102,088 end works + tests 8% 196,00 8,17 4,08 0,00 40,83 0,00 0,00 81,67

Total 100% 2.450,00 106,17 477,75 367,50 367,50 110,25 12,25 1.008,58

Table 1. Investments function of a nuclear power plant (2450 M€UROS, constant 2009)

NOTE: Construction simulation of a 1.000 MW Advance Boiling Water Reactor (ABWR) (similar to the one installed in Cofrentes Nuclear Power Plant)


2.1. Data

Uranium Enrichment Fabrication Equipments Own Personnel

External Personnel Total

Combustible 1,925 1,225 0,35 3,50O&M 1,11 2,59 3,70O&M (replacement) 2,21 0,34 0,85 3,40Decommissioning and final disposal 1 0,5 3,5 5,00

Insurances 0,21Total 1,925 1,225 0,35 4,32 3,43 4,35 15,81%/Total 12,18% 7,75% 2,21% 27,32% 21,70% 27,51% 100,00%

Table 2: Nuclear Fuel Cycle estimation costs and O&M (€/MWh) (2009 prices)

Fuel Cycle phase Operation & Maintenance phase

BASELINE SCENARIO:

- LIFETIME: 60 years Production = 467.164 GWh (~ 4% of electrcity demand per year).

- Load factor assumption = 81,54% Cofrentes NPP production in the last 25 years.

- Disscount rate = from 5 to 6% (Ruesga, 2008).


2.1. Data

DFd (FBKF) DFm (FBKF) DFd DFmT1 Agriculture, Hunting, Forestry and Fishing2 Mining and Quarrying 899,29

from 3 to 78 Coke, Refined Petroleum and Nuclear Fuel 735,78

from 9 to 1213 Machinery, Nec 367,50 482,39 426,59 559,9514 Electrical and Optical Equipment 367,50 521,22 426,59 605,02

from 15 to 1718 Construction 588,00 4,98

from 19 to 28 0,0028 Financial Intermediation 12,25 98,102930 Renting of M&Eq and Other Business Activities 0,00 2.032,1731 Public Admin and Defence; Compulsory Social Security 106,17

from 32 to 351.441 1.009 2.983,45 2.800,05

Operation & MaintenanceConstruction/Investment

Total

Table 3: Final demand (domestic and imported) vectors for the whole life cycle.

NOTE: Sectorial structure WIOD (35 sectors).

Fuel

Cyc

le p

hase


2.1. Data

Figure 1: Spain´s Nuclear Fuel Cycle (IAEA, 2005).

NOTE: Investment phase and rest of O&M distribution between domestic and imported goods comes from WIOD structure.

Uranium (U3O8) Conversion (UF6) Enrichment

Australia Cameco (CANADA) Eurodif (FRANCE)Canada Comurhex (FRANCE) Minatom (RUSSIA)Russia Convedyn (USA) Urenco (GER/NETHERLANDS)Namibia Minatom (RUSSIA) USEC Inc. (USA)Niger WH Springfields (UK)PortugalSouth Africa

Reprocessing Reactors Fabrication

BNFL LWR Belgonucléaire (BELGIUM)Framatome ANP (GERMANY)GNF (USA)WH Columbia (USA)WH Springfields (UK)WH Västeräs (SWEDEN)


2.1. Data

Table 4: Imported Final Demand by region.

DFm (FBKF) RUE NAFTA China EastAsia BRIIAT RoW DFmT RUE NAFTA China EastAsia BRIIAT RoW12 899,29 356,13 326,18 216,98

from 3 to 88 735,78 265,24 222,33 248,22

from 9 to 1210111213 482,39 369,51 18,17 39,41 15,91 7,93 31,44 559,95 428,93 21,09 45,75 18,47 9,21 36,5014 521,22 320,75 22,54 121,79 26,00 13,63 16,50 605,02 372,33 26,16 141,37 30,18 15,82 19,16

from 15 to 1718 4,98 4,88 0,00 0,00 0,00 0,01 0,09

from 19 to 35Total 1.009 695 41 161 42 22 48 2.800,05 1.066 626 187 49 599 273

Construction/Investment Operation & Maintenance

SPAIN Rest of UE NAFTA CHINA BRIIATEAST ASIA RoW


2.2. Methodology

Figure 2: WIOT, aggregation to 7 regions valued in Euros (2009).

1 to 35 1 to 35 1 to 35 1 to 35 1 to 35 1 to 35 1 to 35 Final DemandSPAIN RUE NAFTA China EastAsia BRIIAT RoW SPAIN

1 to 35 SPAIN Ad Am Am Am Am Am Am yd1 to 35 RUE Am Ad Am Am Am Am Am ym RUE1 to 35 NAFTA Am Am Ad Am Am Am Am ym NAFTA1 to 35 China Am Am Am Ad Am Am Am ym China1 to 35 EastAsia Am Am Am Am Ad Am Am ym EastAsia1 to 35 BRIIAT Am Am Am Am Am Ad Am ym BRIIAT1 to 35 RoW Am Am Am Am Am Am Ad ym RoW

(245x245) (245x35)

r

mr

r

rr

rr

r

mmmmmm

m

m

m

my

y

y

y

x

x

x

x

AAAA

AAAA

AAAA

AAAA

x

x

x

x

3

2

1

3

2

1

321

3333231

2232221

1131211

3

2

1 Also expressed in compact form by:

yAxx

Through Leontief Inverse [L= (I – A)-1]:

yAIx 1)(


2.2. Methodology

1 to 35 1 to 35 1 to 35 1 to 35 1 to 35 1 to 35 1 to 35SPAIN RUE NAFTA China EastAsia BRIIAT RoW

1 to 35 SPAIN eWIOD

1 to 35 RUE eWIOD

1 to 35 NAFTA eWIOD

1 to 35 China eWIOD

1 to 35 EastAsia eWIOD

1 to 35 BRIIAT eWIOD

1 to 35 RoW eWIOD

Figure 3: Matrix of emissions coefficients “e” (ktCO2 –eq per million of euros) [WIOD]

NOTE: Matrix e is combined with ECO-INVENT data for the development of the hybrid MRIO-LCA model

ECO-INVENT data for Mining and Quarrying and Coke, Refined Petroleum and Nuclear Fuel


hMRIO-LCA

2.2. Methodology

Summary of models used:

Hybrid Multi-Regional IO model (HMRIO-LCA)

...)(

)(

...)()(

32

321

AALI

AILD

AAAIAIL yAAeAIeF ˆ...)](ˆ)(*ˆ[* 32

ECO-INVENT emissions coefficientsand WIOD emissions coefficients

Multi-Regional IO model (MRIO-LCA)

^1^

yeF AI where e is the WIOD emissions coefficients

Single Region IO model (SRIO-LCA)

^^^ 11^1^

yyAIAAIeyAIemd

SP

mSPdSP

SPd

SPt

SPd

E where eSP is the Spanish(DTA)


2.3. Scenarios

Variable Unit Scenario code Variation

SRIO-LCA A1MRIO-LCA A2hMRIO-LCA (baseline) A3fast built (5y) -10% B1 53 years extension +10% B2 116 years extension +20% B3 14early decommissioning 25Y C1 25intermediate 40Y C2 40long lifetime 100Y C3 1001980 USA (75%) D1 75%intermediate (85%) D2 85%near-full load D3 95%Paner Plan 2020 E1 -35%90% renewables scenario E2 -78%Coal Decree E3 22,80%

g/CO2E. GHG INTENSITY OF ECONOMY

C. LIFETIME years

A. METHODOLOGICAL APPROACH

g/CO2

D. LOAD FACTOR %

B. CONSTRUCTION PERIOD years

Variable Unit Scenario code Variation

EU-Fuel Cycle FA1NAFTA-Fuel Cycle FA2BRIIAT-Fuel Cycle FA3EU-O&M FB1China-O&M FB2BRIIAT-O&M FB3RUE-Construction FC1China-Construction FC2BRIIAT-Construction FC3Double price G1 100%Triple price G2 200%Report OCDE+IEA H1Report MIT 2003 H2Best cases compiled I1Worst cases compiled I2

-----

g/CO2

I. BEST AND WORST CASE g/CO2

F. WORLD CONSUMPTION PATTERN

g/CO2

H. FINANCE COMPARISON

G. URANIUM PRICE g/CO2

Table 5: Summary of scenarios.


3. Main Results

Table 6: CO2 emissions of nuclear electricity by origin of inputs and life cycle stage (g CO2 –eq /Kwh).

Construction Fuel O&M TotalDomestic 0,62 0,01 0,87 1,50Foreign 2,13 13,13 2,94 18,20Total 2,75 13,14 3,81 19,70

Graph 1: CO2 –eq emissions of nuclear electricity by origin of inputs and life cycle stage (g CO2/Kwh).


3. Main Results

Graph 2: CO2 –eq emissions of nuclear electricity by region (gCO2 –eq /Kwh intensities).


Spain

Rest of EU

NAFTA

China

East Asia

BRIIAT

Rest of World

0.00% 5.00% 10.00% 15.00% 20.00% 25.00% 30.00%

Construction Fuel O&M

3. Main Results

Graph 2: hMRIO-LCA Carbon footprint (gCO2 –eq /KWh) by country.

7,6%

21,46%

19,86%

11,21%

27,5%

11,08%

1,28%


3. Main Results

Variable Scenario code Variation Emissions

Construction (gCO2eq/kWh)

Emissions Fuel (gCO2eq/kWh)

EmissionsO&M (gCO2eq/kWh)

Total Emissions (gCO2eq/kWh)

Sensitivity (total/baseline)

SRIO-LCA A1 1,47 3,81 2,02 7,30 -62,97%MRIO-LCA A2 2,69 6,86 3,73 13,28 -32,57%hMRIO-LCA (baseline) A3 2,75 13,14 3,81 19,70 -----fast built (5y) -10% B1 5 2,22 13,14 3,81 19,17 -2,67%3 years extension +10% B2 11 2,71 13,14 3,81 19,67 -0,16%6 years extension +20% B3 14 2,96 13,14 3,81 19,91 1,09%early decommissioning 25Y C1 25 6,59 13,14 3,81 23,54 19,51%intermediate 40Y C2 40 4,12 13,14 3,81 21,07 6,97%long lifetime 100Y C3 100 1,65 13,14 3,81 18,60 -5,57%1980 USA (75%) D1 75% 2,98 13,14 3,81 19,94 1,21%intermediate (85%) D2 85% 2,63 13,14 3,81 19,59 -0,57%near-full load D3 95% 2,36 13,14 3,81 19,31 -1,97%Paner Plan 2020 E1 -35% 2,69 13,14 3,70 19,54 -0,82%90% renewables scenario E2 -78% 2,62 13,14 3,57 19,33 -1,85%Coal Decree E3 22,80% 2,78 13,14 3,88 19,80 0,54%EU-Fuel Cycle FA1 2,75 12,94 3,81 19,49 -1,05%NAFTA-Fuel Cycle FA2 2,75 12,72 3,81 19,27 -2,17%BRIIAT-Fuel Cycle FA3 2,75 13,75 3,81 20,30 3,07%EU-O&M FB1 2,75 13,14 2,99 18,88 -4,14%China-O&M FB2 2,75 13,14 7,35 23,24 17,97%BRIIAT-O&M FB3 2,75 13,14 5,53 21,41 8,71%RUE-Construction FC1 2,11 13,14 3,81 19,07 -3,20%China-Construction FC2 5,50 13,14 3,81 22,45 13,99%BRIIAT-Construction FC3 4,08 13,14 3,81 21,03 6,78%Double price G1 100% 2,75 16,49 3,81 23,04 16,98%Triple price G2 200% 2,75 19,83 3,81 26,39 33,97%Report OCDE+IEA H1 2,76 13,84 4,01 20,62 4,66%Report MIT 2003 H2 3,22 46,23 13,40 62,86 219,12%Best cases compiled I1 1,91 3,35 3,81 9,06 -54,00%Worst cases compiled I2 7,72 62,45 13,40 83,58 324,28%

G. URANIUM PRICE


I. BEST AND WORST CASE

-----


B. CONSTRUCTION PERIOD

C. LIFETIME

D. LOAD FACTOR

E. GHG INTENSITY OF ECONOMY

F. WORLD CONSUMPTION PATTERN

Table 7: Scenarios results


Estimated (gCO2/Kwh)

OECD 25.09ISA (Aus) 8.2Extern-E (UK) 11.58

Paper: BARNABY AND KEMP, 2007

3. Main Results

Variable Unit Scenario code Variation Emissions





Sensitivity (total/basel

ine)

SRIO-LCA A1 1,47 3,81 2,02 7,30 -62,97%MRIO-LCA A2 2,69 6,86 3,73 13,28 -32,57%hMRIO-LCA (baseline) A3 2,75 13,14 3,81 19,70 -----


g/CO2

Table 7 (excerpt): Methodological scenarios.

Comparison with other studies. Comparison with other technologies.


Estimated (gCO2/Kwh) %

Frontend (Fuel) 25.09 37.97%Construction 8.2 12.41%O & M (Fuel) 11.58 17.52%Backend 9.29 13.92%Deommissioning 12.01 18.17%TOTAL 66.08 100.00%

Survey: SOVACOOL, 2008

CapacityEstimated

(gCO2/Kwh)Wind offshore 2.5 Mw 9Wind onshore 1.5 MW 10Hydro 3.1 MW 10Solar Thermal 80 MW 13Biomass Various 14-31NUCLEAR (hMRIO-LCA)

1000 MW 19.7

Geothermal 80 MW 38Natural Gas Various 443Diesel Various 778Coal Various 960-1050

Survey: SOVACOOL, 2008

3. Main Results







ine)

fast built (5y) -10% B1 5 2,22 13,14 3,81 19,17 -2,67%3 years extension +10% B2 11 2,71 13,14 3,81 19,67 -0,16%6 years extension +20% B3 14 2,96 13,14 3,81 19,91 1,09%1980 USA (75%) D1 75% 2,98 13,14 3,81 19,94 1,21%intermediate (85%) D2 85% 2,63 13,14 3,81 19,59 -0,57%near-full load D3 95% 2,36 13,14 3,81 19,31 -1,97%Paner Plan 2020 E1 -35% 2,69 13,14 3,70 19,54 -0,82%90% renewables scenario E2 -78% 2,62 13,14 3,57 19,33 -1,85%Coal Decree E3 22,80% 2,78 13,14 3,88 19,80 0,54%

g/CO2E. GHG INTENSITY OF ECONOMY

D. LOAD FACTOR %

B. CONSTRUCTION PERIOD

years

Table 7 (excerpt): Construction phase, Load factor and GHG intensities scenarios.

MAIN IDEAS:B and D There are not big impacts over Carbon Footprint about uncertainties related to the lenght of construction phase and to Load factor operation.

E As Spain main emissions are produced outside Spain (internationalized nuclear industry) changes in domestic energy mix has not too much impact over Carbon Footprint.


3. Main Results







ine)

early decommissioning 25Y C1 25 6,59 13,14 3,81 23,54 19,51%intermediate 40Y C2 40 4,12 13,14 3,81 21,07 6,97%long lifetime 100Y C3 100 1,65 13,14 3,81 18,60 -5,57%

C. LIFETIME years

Table 7 (excerpt): Lifetime scenarios.

MAIN IDEAS:• Early decommissioning scenarios, related to new and unexpected energy policies (like the

shutdown of nuclear energy generation in Germany after Fukushima) would generate an increase on emissions by almost 20%.

• 40 years lifetime generates similar results.• 100 years of operation do not reduce too much the amount of emissions.

The less lifetime the more emissions in construction phase








ine)

EU-Fuel Cycle FA1 2,75 12,94 3,81 19,49 -1,05%NAFTA-Fuel Cycle FA2 2,75 12,72 3,81 19,27 -2,17%BRIIAT-Fuel Cycle FA3 2,75 13,75 3,81 20,30 3,07%EU-O&M FB1 2,75 13,14 2,99 18,88 -4,14%China-O&M FB2 2,75 13,14 7,35 23,24 17,97%BRIIAT-O&M FB3 2,75 13,14 5,53 21,41 8,71%RUE-Construction FC1 2,11 13,14 3,81 19,07 -3,20%China-Construction FC2 5,50 13,14 3,81 22,45 13,99%BRIIAT-Construction FC3 4,08 13,14 3,81 21,03 6,78%

-----F. WORLD CONSUMPTION PATTERN

g/CO2

Table 7 (excerpt): World consumption patterns scenarios.

3. Main Results

MAIN IDEAS:• Changes in consumption patterns of some phases are relevant.• Fuel Cycle is a high pollutant phase, differences between patterns are not too different to Baseline.• O&M If China-Spain trade relationships would be higher and higher, total Carbon Footprint would

be almost a 18% higher.• Construction If the amount of Chinese construction phase inputs would be higher, Carbon

Footprint almost 14%.• All the scenarios show a reduction of the Carbon Footpint if EU produce the inputs. REASON: The

cleaner energy mix.


3. Main Results







ine)

Double price G1 100% 2,75 16,49 3,81 23,04 16,98%Triple price G2 200% 2,75 19,83 3,81 26,39 33,97%Report OCDE+IEA H1 2,76 13,84 4,01 20,62 4,66%Report MIT 2003 H2 3,22 46,23 13,40 62,86 219,12%Best cases compiled I1 1,91 3,35 3,81 9,06 -54,00%Worst cases compiled I2 7,72 62,45 13,40 83,58 324,28%

g/CO2

I. BEST AND WORST CASE

g/CO2


G. URANIUM PRICE g/CO2

Table 7 (excerpt): Uranium prices, Financial comparison and Bests and Worts scenarios.

MAIN IDEAS:• The scarcity of Uranium in the world, and the subsequent increase of prices related to the exploit of

new mining deposists would increase the Carbon Footprint a 34% (x3) and a 17% (x2).

• If we use financial data from OECD and IEA report, Carbon Footprint woul be similar. • If we use the MIT 2003 report data, Carbon Footprint would be a 220% higher (closer to fossil fuels).

• Adding best and worst scenarios, the interval of emissions depending on the uncertainties considered goes from 9 gCO2/kWh to 83,58 gCO2/Kwh (Fuel Cycle highest responsability).o Taking into consideration the variability and uncertainties is crucial to estimate nuclear power

Carbon Footprint properly.


4. Conclusions

The Hybrid MRIO-LCA is the most accurate model to evaluate the Nuclear Power plant Carbon Footprint.

The consideration of uncertainties and variability is crucial. Most of the studies presents very different results depending on the variables and assumptions considered.

Nuclear Spanish industry was dismantled because of the nuclear moratorium since eighties.

The use of the MRIO model allow to enhance the role of imports in a Spanish Nuclear Power plant life cycle (almost 90%), concentrated in the Fuel Cycle phase.


Baseline19,70 gCO2 –eq

/kWh

4. Conclusions

The scenarios with a higher influence over emissions are: METHOLODGY LIFETIME CONSUMPTION PATTERNS URANIUM PRICES FINANCIAL DATA SETS

Fuel cycle is the most pollutant phase. Most of emissions are produced in BRIIAT.

Uncertainties captured by the multiple scenarios simulated. Results are coherent with other reference studies.

Low Carbon Footprint compared to other technologies.

BEST CASE: 9,06 gCO2 –eq /kWh WORST CASE: 83,58 gCO2 –eq /kWh


THANKS FOR YOUR ATTENTION!Carbon footprint of the nuclear energy using IO-LCAJorge E. Zafrillaa, María Ángeles Cadarsoa, Fabio Monsalvea y Cristina de la Rúab

a Universidad de Castilla-La Mancha, Albaceteb Centro de Investigaciones Energéticas, Medioambientales y Tecnológicas

E-mail: [email protected]

IX Congreso Asociación Española para la Economía EnergéticaMadrid, 3 y 4 de febrero de 2014

Documents

Carbon footprint of the nuclear energy using IO-LCA Jorge E. Zafrilla a, María Ángeles Cadarso a, Fabio Monsalve a y Cristina de la Rúa b a Universidad